Triple
T2283280
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zebedee |
E51327
|
entity |
| Predicate | hasEmployees |
P36133
|
FINISHED |
| Object | hired servants |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: hired servants | Statement: [Zebedee, hasEmployees, hired servants]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEmployees Context triple: [Zebedee, hasEmployees, hired servants]
-
A.
employedPeople
Indicates that there exists a relationship where people are currently working in jobs or positions, typically under an employer.
-
B.
hasNumberOfCompanies
Indicates the quantitative relationship specifying how many companies are associated with a given entity.
-
C.
hasWorkforceType
Indicates the type or category of workforce associated with an entity (such as permanent, temporary, contract, or part-time).
-
D.
employedApproximately
Indicates that one entity employs another in a manner where the number, duration, or extent of employment is approximate rather than exact.
-
E.
hasMajorEmployer
Indicates that an entity has a primary or most significant employer with which it is chiefly affiliated for work or occupation.
- F. None of above. chosen
Provenance (4 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69a88b08e4308190bdac9aebcca1c91a |
completed | March 4, 2026, 7:42 p.m. |
| NER | Named-entity recognition | batch_69abc21d6d748190980128c1bc5b9621 |
completed | March 7, 2026, 6:13 a.m. |
| PD | Predicate disambiguation | batch_69abbdbb9e4c819085fc588626ec7c09 |
completed | March 7, 2026, 5:55 a.m. |
| PDg | Predicate description generation | batch_69abbe1ecb7081909c2c66da08a48ab7 |
completed | March 7, 2026, 5:56 a.m. |
Created at: March 4, 2026, 7:48 p.m.